Money on the mound…Baseball Pitcher’s Salary

Money on the mound…Baseball Pitcher’s Salary

By – Group 10

Parag DeshpandeKevin BrunettiKevin BursonRebecca HardingEduardo SantanaBrooke Straiton

and why are they so costly?

FOX School of Business

MIS 5401 Final Project

Team Salaries and Player Salaries Data for 2014

4/10 highest paid players were Pitchers

Top 10 Team Salaries

Top 10 Player Salaries

FOX School of Business, MIS 5401 – Final Project

Pitcher Pitcher Pitcher Pitcher

Team Salaries and Team Wins Data for 2014

• Started looking at the Team Salaries v/s Team Wins

• LA Dodgers had highest team salary of $230M with 94 wins

• Miami Marlins had lowest team salary of $46M with 76 wins

So we drilled down to understand the relation between pitcher’s salary and wins

FOX School of Business, MIS 5401 – Final Project

Team Wins and Pitcher’s Salary (% of Team’s Total Salary) Data for 2014

• Philadelphia Phillies spent 53.43% of team’s total salary on pitchers and had 73 wins

• LA Angels of Anaheim had highest wins 98, with 33.7% of team’s total salary spent on pitchers

FOX School of Business, MIS 5401 – Final Project

Data reveals that the pitcher’s cost

Data for 2014

of the team’s total salary 33.16%Salary

Rest of the team Pitcher

on average

Thus we dug deeper and modeled the pitcher’s salary

33.16 %

FOX School of Business, MIS 5401 – Final Project

The Key Data Points Data for 2014

• Master data – for player ID, positions and names• Teams table – for team ID, Games, Wins• Salary table – for player’s ID and salaries• Pitching table – for player’s performance based on

Games Wins Strike Outs Walks Earned Run Average Home Runs

Extracted - transformed - loaded the data to analyze itExported to JMP statistical software to analyze it further

FOX School of Business, MIS 5401 – Final Project

How to calculate a Pitcher’s Salary..? Data for 2014

Pitcher’s Salary =

Multiple regression model derived from JMP statistical software

3243277.3 – (18530.17 x Walks) – (3951.79 x Earned Run Average) + (36671.24 x Strike Outs) – (48733.19 x Wins) – (49926.59 x Games) + (57007.92 x Home Runs) + (3877779.7 x Opponent’s Batting Average)

FOX School of Business, MIS 5401 – Final Project

How did we reach the model? Data for 2014

Multiple regression model derived from JMP statistical software

We used Salary table and Pitching data table for Pitcher's parameters like• Player Salary• Games• Wins• Strike Outs• Walks• Earned Run Average• Home Runs Hit

R2 = 21.29%

FOX School of Business, MIS 5401 – Final Project

Conclusion Data for 2014

It is possible to mathematically model a salary of a pitcher!But salary will not always depend on the mathematical model

Further attributes might make impact• Years of experience• Fame and glamor• Value to the team and increase in team fan following

Using this model it is difficult to predict a salary of a pitcher who is about to debut in professional league

FOX School of Business, MIS 5401 – Final Project

References1. Armand, E. & Lily, M. (2015, April 10). How much does your baseball team cost?. Los Angeles Times. Retrieved from http://graphics.latimes.com/mlb-salaries-2015/

2. Society for American Baseball Research (n.d.) A Guide to Sabermetric Research. Retrieved from http://sabr.org/sabermetrics

3. Jim, A (n.d.) An Introduction to Sabermetrics. Retrieved from http://www-math.bgsu.edu/~albert/papers/saber.html

4. Lahman’s Baseball Database. (2014). 2014 – comma-delimited version – Updated January 24, 2015 Retrieved from http://www.seanlahman.com/baseball-archive/statistics

FOX School of Business, MIS 5401 – Final Project

Money on the mound…Baseball Pitcher’s Salary

Questions..?

Thank You